mlsanityData to 14 Oct 2026

SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings

arXiv 1911.08743 ↗First posted 20 Nov 2019cs.CL cs.AI cs.IRcited by 2

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Abstract (arXiv)

We describe our system for finding good answers in a community forum, as defined in SemEval-2016, Task 3 on Community Question Answering. Our approach relies on several semantic similarity features based on fine-tuned word embeddings and topics similarities. In the main Subtask C, our primary submission was ranked third, with a MAP of 51.68 and accuracy of 69.94. In Subtask A, our primary submission was also third, with MAP of 77.58 and accuracy of 73.39.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Nov 2019.

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